[R] Goodness of fit test in fitdistrplus
I am using the fitdistrplus package in R and would like to do a goodness of fit test. But there does not seem to be any option to do that. Any ideas on how I can do that? Thanks Regards, Indrajit [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] goodness of fit test for 2-dimensional data in R
Hi, I have a certain number of paired data that show errors at the x-axis and y-axis for the location of a target and is below. My aim is to fit a distribution to the uncertain location of the target via certain tests such as Chi-square test (if possible). I was wondering how it can be done in R. Thanks in advance, Yasin x error y error 5.5 -0.5 7 -2 -8 -7.5 6 -1 -1.5 -1 8 2 -2 -2 7 -10 2 -4 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] goodness-of-fit test
Skew as they are, your data certainly don't look normal. Try lognormal. The chi-square test gives good results when all counts are 5 or more, hence the warning. At 12:25 AM 11/12/2010, Andrew Halford wrote: Hi All, I have a dataset consisting of abundance counts of a fish and I want to test if my data are poisson in distribution or normal. My first question is whether it is more appropriate to model my data according to a poisson distribution (if my test says it conforms) or use transformed data to normalise the data distribution? I have been using the vcd package gf-goodfit(Y,type= poisson,method= MinChisq) but i get the following error message Warning message: In optimize(chi2, range(count)) : NA/Inf replaced by maximum positive value I then binned my count data to see if that might help V1 V2 1 5 34 2 10 30 3 15 10 4 20 8 5 25 7 6 30 0 7 35 3 8 40 2 9 45 3 10 50 1 11 55 0 12 60 1 but still received an error message Goodness-of-fit test for poisson distribution X^2 df P( X^2) Pearson 2573372 330 Warning message: In summary.goodfit(gf) : Chi-squared approximation may be incorrect Am I getting caught out because of zero counts or frequencies in my data? Andy -- Andrew Halford Ph.D Associate Research Scientist Marine Laboratory University of Guam Ph: +1 671 734 2948 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: r...@lcfltd.com Least Cost Formulations, Ltd.URL: http://lcfltd.com/ 824 Timberlake Drive Tel: 757-467-0954 Virginia Beach, VA 23464-3239Fax: 757-467-2947 Vere scire est per causas scire __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] goodness-of-fit test
Hi All, I have a dataset consisting of abundance counts of a fish and I want to test if my data are poisson in distribution or normal. My first question is whether it is more appropriate to model my data according to a poisson distribution (if my test says it conforms) or use transformed data to normalise the data distribution? I have been using the vcd package gf-goodfit(Y,type= poisson,method= MinChisq) but i get the following error message Warning message: In optimize(chi2, range(count)) : NA/Inf replaced by maximum positive value I then binned my count data to see if that might help V1 V2 1 5 34 2 10 30 3 15 10 4 20 8 5 25 7 6 30 0 7 35 3 8 40 2 9 45 3 10 50 1 11 55 0 12 60 1 but still received an error message Goodness-of-fit test for poisson distribution X^2 df P( X^2) Pearson 2573372 330 Warning message: In summary.goodfit(gf) : Chi-squared approximation may be incorrect Am I getting caught out because of zero counts or frequencies in my data? Andy -- Andrew Halford Ph.D Associate Research Scientist Marine Laboratory University of Guam Ph: +1 671 734 2948 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Goodness of fit test for count data
Dear all, I am trying to test goodness of fit. I assume that a data follow Poisson or Negative binomial distribution. I can test the goodness of fit in case of no truncated data. However, I could not find any good function or packages when a data is truncated. For example, a frequency table for the number of visiting emergency room in one hundred one observations past one year is as follow: N freq 1 30 2 35 3 26 4 8 5 0 6 2 7 0 I expect the frequency table to satisfy a Poisson distribution or Negative binomial distribution. However, the distribution is different from the usual Poisson or Negative binomial distribution because one value, zero, is excluded. I expect that the distribution is zero truncated distribution. In case of SAS, I used NLMIXED procedure to calculate the expected probability when y=1 … y=n under the assumption that a data follows Poisson or Negative binomial distribution. And then I run Chi-square test. If you need the SAS code, I will send E-mail. I want to run this test in R. Could you suggest any idea that can I perform this test in R. Have a nice day. -- View this message in context: http://n4.nabble.com/Goodness-of-fit-test-for-count-data-tp1564963p1564963.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Goodness of fit test for count data
You can compute the conditional probability that your variable equals k given that it is non-zero. For example, if X has poisson distribution with parameter lambda then P(X=k/X!=0) = P(X=k)/(1-P(X=0)) = (exp(-lambda)/(1-exp(-lambda))*lambda^k/k! Now you can find lambda for which the sum of squares of your errors is minimal and then use CHi-aquared test using these expected frequencies. Similarly for negative binomial distribution. --- On Tue, 23/2/10, pinusan anh...@msu.edu wrote: From: pinusan anh...@msu.edu Subject: [R] Goodness of fit test for count data To: r-help@r-project.org Received: Tuesday, 23 February, 2010, 6:11 AM Dear all, I am trying to test goodness of fit. I assume that a data follow Poisson or Negative binomial distribution. I can test the goodness of fit in case of no truncated data. However, I could not find any good function or packages when a data is truncated. For example, a frequency table for the number of visiting emergency room in one hundred one observations past one year is as follow: N freq 1 30 2 35 3 26 4 8 5 0 6 2 7 0 I expect the frequency table to satisfy a Poisson distribution or Negative binomial distribution. However, the distribution is different from the usual Poisson or Negative binomial distribution because one value, zero, is excluded. I expect that the distribution is zero truncated distribution. In case of SAS, I used NLMIXED procedure to calculate the expected probability when y=1 … y=n under the assumption that a data follows Poisson or Negative binomial distribution. And then I run Chi-square test. If you need the SAS code, I will send E-mail. I want to run this test in R. Could you suggest any idea that can I perform this test in R. Have a nice day. -- View this message in context: http://n4.nabble.com/Goodness-of-fit-test-for-count-data-tp1564963p1564963.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Goodness of fit test / pseudo r^2 measure for Zero Inflated Model
Hi I have been using a Zero-Inflated negative binomial model fitted using the pscl zeroinfl command but I would like to extract a goodness of fit measure are there any suitable pseudo R^2 measures available for this type of analysis to try and assess the amount of variation in the data explained by the model? I have tried with the pR2 command in pscl (for computing various pseudo R2 measures), the same package as zeroinfl, but I get the message that there is no-applicable method when I try it with a zeroinfl model. Any suggestions most appreciated. Many thanks in advance Lara [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] goodness of fit test
Hi Edna, You could use lapply or sapply to perform the multiple goodness of fit tests at the same time. Chunhao Quoting Edna Bell [EMAIL PROTECTED]: Dear R Gurus; Is there an automated process for goodness of fit tests, please? I know there is prop.test for one at a time, but I was wondering about this, please. Thanks, Edna Bell __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] goodness of fit test
Dear R Gurus; Is there an automated process for goodness of fit tests, please? I know there is prop.test for one at a time, but I was wondering about this, please. Thanks, Edna Bell __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Goodness of fit test
Dear R users, I have some data sets and I'd want to test if they are genarated under different probability functions. That is, some of them by gamma distribution, exponential one etc. Could anybody propose me any test (or procedure) to see that. I search something similar to the normality tests. Thanks in advance Martín Gastón __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
